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This paper aims to examine how multi-sensory cues, when store-congruent, influence consumer browsing behaviour and its subsequent effect on purchasing.

Two studies were used with a field experimental design in a furnishing retail store to examine browsing behaviour and purchasing in a visual, auditory, olfactory and a multi-sensory treatment group. Data were gathered over 12 weeks. This study was a set of studies comprising my dissertation thesis (Helmefalk, 2017).

Findings show that multi-sensory cues in a retail atmosphere are evidently influencing purchasing via browsing behaviour as a mediator.

The findings evidence browsing behaviour as a mediator and predictor for purchasing, which emphasizes its conceptual and empirical contribution in terms of modifying retail atmospheres. The work contributes to the field of retailing, sensory marketing and consumer behaviour, a novel view on the linkages between multi-sensory cues, browsing behaviour and purchasing.

Online reviews have shown important information that affects consumers’ online shopping behavior. However, little research has examined how they may influence consumers’ online impulse buying behavior. The purpose of this paper is to bring theoretical and empirical connections between them.

The framework of this study was tested on three popular online group shopping websites in China (ju.taobao.com, dianping.com, and meituan.com). An online survey with 315 participants who had experience using these websites was recruited to verify the effects of consumers’ perceived value from reading online reviews on urge to buy impulsively and impulse buying behavior.

The empirical findings show that consumers’ perceived utilitarian and hedonic value from reading online reviews enhance their browsing behavior. Browsing positively affects consumers’ urge to buy impulsively and finally affects their impulse buying behavior. Further, this study finds that consumers with high impulsiveness focus more on hedonic value of online reviews, whereas consumers with low impulsiveness put more emphasis on utilitarian value. Browsing demonstrates a stronger effect on urge to buy impulsively for consumers with high impulsiveness.

This study is one of the early studies to investigate the relationship between social influence (e.g. influence of online reviews) and impulse buying. It draws upon the perspectives of browsing and consumer’s perceived value from the literature. This research also considers consumer differences regarding the level of impulsiveness.

This study aims to investigate and compare mobile and desktop user search behaviours of the 1300K site, a Korean shopping search engine, by using transaction log analysis.

Transaction logs of 1300K site were collected over a three months’ period, from 1 January to 31 March 2018. The data set of this study consists of 1,149,690 desktop queries, 2,346,938 mobile queries, 2,481,747 desktop browsing activities and 2,550,309 mobile browsing activities. This study quantitatively analyses transaction log of 1300K site.

The results of this study show that mobile usage is higher than desktop usage: there are more mobile sessions than desktop sessions and the number of mobile queries is more than double of desktop queries. Overall, mobile query search behaviours are more simple, targeted and focused than desktop query search behaviours. Also, mobile browsing behaviours are more simple and passive than desktop browsing behaviours. However, mobile click behaviours are more active than desktop click behaviours.

To the best of the authors’ knowledge, this study appears to be the first of its type in Korea that compared search behaviours of a large number of users on desktop computers and mobile phones. To identify various characteristics of user search behaviours, this study analyses users’ directory browsing behaviour and click behaviour as well as query search behaviour. The results of this study can be implemented to address the effective improvement and development of search services and interfaces for different devices.

This study is to propose a more effective and efficient analytic methodology based on within-site clickstream associated with path visualization to explore the channel dependence of consumers' latent shopping intent and the related behaviors, with which in turn to gain insight concerning the interactivity between webpages.

The primary intention of the research is to design and develop a more effective and efficient approach for exploring the consumers' latent shopping intent and the related behaviors from the clickstream data. The proposed methodology is to use text-mining package, consisting of the combination of hierarchical recurrent neural networks and Hopfield-like neural network equipped with Laplacian-based graph visualization to visualize the consumers' browsing patterns. Based on the observed interactivity between webpages, consumers' latent shopping intent and the related behaviors can be understood.

The key finding is to evidence that consumers' latent shopping intent and related behaviors within website depend on channels the consumers click through. The accessing consumers through channels of paid search and display advertising are identified and categorized as goal-directed and exploratory modes, respectively. The results also indicate that the effect of the content of webpage on the consumer's purchase intent varies with channels. This implies that website optimization and attribution of online advertising should also be channel-dependent.

This is important for the managerial and theoretical implications: First, to uncover the channel dependence of consumer's latent shopping intent and browsing behaviors would be helpful to the attribution of the online advertising for the sales promotion. Second, in the past, webmasters did not understand users' preferences and make decisions of reorganization purely on the user's browsing path (sequential page view) without appraising psychological perspective, that is, user's latent shopping intent.

This study is the first to explore the channel dependences of consumer's latent shopping intent and the related browsing behaviors through within-site clickstream associated with path visualization. The findings are helpful to the attribution of the online advertising for the sales promotion and useful for webmasters to optimize the effectiveness and usability of their websites and in turn promote the purchase decision.

Enterprises build online product community to expect users to contribute: opinion sharing (content contribution) and product consumption (product contribution). Previous literature rarely focused on both. The purpose of this paper is to explain user contribution mechanism by identifying content contribution and product contribution.

This research chose Xiaomi-hosted online product community (bbs.xiaomi.cn) and Huawei-hosted online product community (club.huawei.com) where users can freely share ideas and buy products at the same time. Data were crawled from 109,665 community users to construct dependent variable measurement, and 611 questionnaires were used to verify research hypotheses.

The results indicate that both cognitive needs and personal integration needs have a significant positive impact on browse behavior; social integration needs and hedonic needs have a significant positive impact on content contribution behavior. Browse behavior not only directly affects but also indirectly influences product contribution through content contribution behavior.

Findings of this research provide community managers with useful insights into the relationship between content contribution and product contribution.

This study explains the formation mechanism of user product contribution and reveals the relationship between user content contribution and product contribution in online product community. This paper provides a different way of theorizing user contributions by incorporating uses and gratifications theory into the “Motivation-Behavior-Result” framework.

Cross-border e-commerce live streaming morphs into an epidemic shopping scenario, yet there is a paucity of research on impulse purchasing in this context. The purpose of this study is to empirically investigate the adoption motivation of cross-border e-commerce live streaming and its influence mechanism on intrinsic response and purchase impulse and to highlight the mediating role of browsing behavior.

Based on the use and gratification lens, a new conceptualization model is established to captivate the theoretical relationships between perceived stimuli, individual attitudes, browsing behavior and impulsive purchases. A questionnaire survey was used to collect cross-sectional data from 427 Malaysian consumers and the estimated framework was validated through AMOS-structural equation modeling technique.

The findings confirm that perceived interactivity, perceived information usefulness and perceived enjoyment significantly influenced positive attitudes toward live-streaming, which in turn induced impulsive purchases; however, perceived affective gratification did not stimulate positive attitudes. Consumers’ utilitarian browsing had a stronger effect on impulse purchases than hedonic browsing and utilitarian browsing behavior mediated the relationship between positive attitudes and impulse buying; however, hedonic browsing had neither a direct nor a mediating effect on impulsive purchases.

This research enhances the literature on the impact of cross-border e-commerce live streaming, an emerging technology, on consumer behavior and offers managerial implications for e-commerce practitioners to gain insights into consumer impulse purchasing behavior.

The findings revamp conventional knowledge and provide new angles for understanding the formation mechanisms of impulse purchases, motivations for virtual media use and browsing behavior mediating effects in the context of live streaming.

The purpose of this paper is to examine the structural relationship between web site personality, utilitarian web browsing, hedonic web browsing and online impulse buying of tourism products.

A total of 405 valid online questionnaires were collected to empirically test the measurement and structural model using partial least square path modelling approach, a variance-based structural equation modelling technique. The study sample includes experienced online shoppers who performed shopping tourism products and services via internet medium.

The results imply that web site personality is a second-order reflective construct comprising solidity, enthusiasm, genuineness, sophistication and unpleasantness. web site personality positively influences utilitarian web browsing, hedonic web browsing and online impulse buying; and both hedonic web browsing and utilitarian web browsing positively influence online impulse buying.

Online impulse buying of tourism products has not been profoundly explored in current literature, despite its important implication for managers, academicians and consumers alike. This study contributes to the field of e-commerce marketing, retailing and e-tourism research.

The purpose of this paper is to propose customer behavior analysis based on real-time data processing and association rule for digital signage-based online store (DSOS). The real-time data processing based on big data technology (such as NoSQL MongoDB and Apache Kafka) is utilized to handle the vast amount of customer behavior data.

In order to extract customer behavior patterns, customers’ browsing history and transactional data from digital signage (DS) could be used as the input for decision making. First, the authors developed a DSOS and installed it in different locations, so that customers could have the experience of browsing and buying a product. Second, the real-time data processing system gathered customers’ browsing history and transaction data as it occurred. In addition, the authors utilized the association rule to extract useful information from customer behavior, so it may be used by the managers to efficiently enhance the service quality.

First, as the number of customers and DS increases, the proposed system was capable of processing a gigantic amount of input data conveniently. Second, the data set showed that as the number of visit and shopping duration increases, the chance of products being purchased also increased. Third, by combining purchasing and browsing data from customers, the association rules from the frequent transaction pattern were achieved. Thus, the products will have a high possibility to be purchased if they are used as recommendations.

This research empirically supports the theory of association rule that frequent patterns, correlations or causal relationship found in various kinds of databases. The scope of the present study is limited to DSOS, although the findings can be interpreted and generalized in a global business scenario.

The proposed system is expected to help management in taking decisions such as improving the layout of the DS and providing better product suggestions to the customer.

The proposed system may be utilized to promote green products to the customer, having a positive impact on sustainability.

The key novelty of the present study lies in system development based on big data technology to handle the enormous amounts of data as well as analyzing the customer behavior in real time in the DSOS. The real-time data processing based on big data technology (such as NoSQL MongoDB and Apache Kafka) is used to handle the vast amount of customer behavior data. In addition, the present study proposed association rule to extract useful information from customer behavior. These results can be used for promotion as well as relevant product recommendations to DSOS customers. Besides in today’s changing retail environment, analyzing the customer behavior in real time in DSOS helps to attract and retain customers more efficiently and effectively, and retailers can get a competitive advantage over their competitors.

The problem of privacy protection in digital libraries is causing people to have increasingly extensive concerns. This study aims to design an approach to protect the preference privacy behind users’ book browsing behaviors in a digital library.

This paper proposes a client-based approach, whose basic idea is to construct a group of plausible book browsing dummy behaviors, and submit them together with users’ true behaviors to the untrusted server, to cover up users’ sensitive preferences.

Both security analysis and evaluation experiment demonstrate the effectiveness of the approach, which can ensure the privacy security of users’ book browsing preferences on the untrusted digital library server, without compromising the usability, accuracy and efficiency of book services.

To the best of the authors’ knowledge, this paper provides the first attempt to the protection of users’ behavior privacy in digital libraries, which will have a positive influence on the development of privacy-preserving libraries in the new network era.